Poster abstract: MDP framework for sensor network coordination

Authors:
Shuping Liu;Anand Panangadan;Ashit Talukder;Cauligi S. Raghavendra
Affiliations:
University of Southern California, Ming Hsieh Department of Electrical Engineering, Los Angeles, 90089, USA;Childrens Hospital Los Angeles, 4650 Sunset Blvd., CA 90027, USA;University of Southern California, Ming Hsieh Department of Electrical Engineering, Los Angeles, 90089, USA;University of Southern California, Ming Hsieh Department of Electrical Engineering, Los Angeles, 90089, USA
Venue:
IPSN '09 Proceedings of the 2009 International Conference on Information Processing in Sensor Networks
Year:
2009

Citing 2
Cited 1

Wireless sensor networks

Wireless sensor networks
Markov decision processes for control of a sensor network-based health monitoring system

IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3

Evaluation of learning algorithms for optimal policy representation in sensor-network based human health monitoring systems

ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We consider a body area network application of monitoring a patient continuously [1,2]. In this application, several sensors are used in measuring physiological and metabolic readings of a patient. In such a system, the sampling rates have to be coordinated to maximize the life time of this sensor network system. We formulate the relationship between energy consumption, sensor sampling rates, and utility of coordination as a Markov Decision Process and compute a globally optimal policy for sensor sampling rates. We then present an entropy-based mechanism for communication between nodes to execute this global policy. We show preliminary results on simulated data to demonstrate that this distributed control framework is feasible for a limited number of sensors.